class_docstr: An interface class to different DiCE implementations.
docstr: Init method
  
  :param data_interface: an interface to access data related params.
  :param model_interface: an interface to access the output or gradients of a trained ML model.
  :param method: Name of the method to use for generating counterfactuals
docstr_tok: ["Init","method",":","param","data_interface",":","an","interface","to","access","data","related","params",".",":","param","model_interface",":","an","interface","to","access","the","output","or","gradients","of","a","trained","ML","model",".",":","param","method",":","Name","of","the","method","to","use","for","generating","counterfactuals"]
code: def __init__(
      self, data_interface, model_interface, method="random", **kwargs
  ):
      """Init method
  
      :param data_interface: an interface to access data related params.
      :param model_interface: an interface to access the output or gradients of a trained ML model.
      :param method: Name of the method to use for generating counterfactuals
      """
      self.decide_implementation_type(
          data_interface, model_interface, method, **kwargs
      )
  
file_path: DiCE/dice_ml/dice.py
imports: from raiutils.exceptions import UserConfigValidationException
  from dice_ml.constants import BackEndTypes, SamplingStrategy
  from dice_ml.data_interfaces.private_data_interface import PrivateData
  from dice_ml.explainer_interfaces.explainer_base import ExplainerBase
label_desc: Use image node_id 1 to create a new Dice object from inherited base classes: ExplainerBase with example: obj = Dice(data_interface, model_interface, method)